This invention relates generally to systems and methods for managing use of energy, and especially to systems and methods for managing energy use in a complex multi-building context.
A number of factors have combined in recent years to create an electrical energy crisis in many regions of the United States. These include: a shortage of generating capacity; lack of capital investment in new transmission capacity; fuel volatility; and increased demand. The result is a power shortage and difficulties in the energy infrastructure.
Multiple-building systems, such as commonly owned systems of 30, 60 or more buildings, exist throughout the world today. Examples of such building systems include, e.g., university systems. Multiple building systems may be geographically dispersed. Controlling energy consumption, and costs of energy consumption, in such wide-spread building systems presents challenges. See, e.g., U.S. Pat. No. 6,178,362 issued in 2001 to Woolard et al. (assigned to Silicon Energy Corp.), discussing some of the problems of energy management and energy cost management for commercial users who operate large physical plants.
Conventionally, if it was desired to reduce energy consumption by a particular amount (such as a 40 KW reduction in the next two hours) in a multi-building system, which typically use procedure-based systems (such as conventional building management systems, current-generation energy management software, or SCADA-type systems), the building manager was required to conduct all the steps and tasks necessary to accomplish the goal manually. Thus, the question of how to accomplish a specified energy consumption reduction has been heavily human-dependent.
Another question is how to know what specific energy consumption reduction to even want to accomplish. That question, too, has been heavily human-dependent. For example, conventionally, as in U.S. Pat. No. 6,178,362, various meters and data-taking devices have been included in multi-building systems, but the obtained energy data still must be reviewed by a human operator. The necessary inclusion of a human operator in conventional systems has posed certain substantial disadvantages. A human operator may fail to recognize one or more energy-relevant events (such as the threat of a new maximum peak). The diligence, accuracy, speed, and foresight of a human operator necessarily may be limited, contributing to likely missed recognition of such energy relevant events. Human operators may have other duties, so that they not be reviewing relevant energy data at what would be a critical time. Human operators may review data yet fail to appreciate its significance. Human operators may review data, appreciate its significance, and decide on a course of action that may be less than optimal in terms of cost or convenience or comfort.
In any energy management system, reaching a new maximum of peak usage will be expensive and is acknowledged as something to be recognized—and avoided. In a human-based energy management system, the human operator may, or may not, be looking at energy data output at a time when the data is surging towards a new peak. Human operators come in a variety of diligence, attentiveness, and ability levels. Human operators tasked with recognizing surges towards new peaks tend to have other tasks, such that they cannot provide a sufficient level of attention and monitoring to recognize every surge towards a new peak.
Recognition of an energy-relevant event such as a surge towards a new peak is only one aspect of energy management. After recognition that an undesirable energy-relevant event is in progress, there remains the question of what response to take. There is only so much information and so many permutations that a human operator possibly can take into account in a fixed amount of time. The human operator is called upon to decide and act quickly, to avoid the new peak toward which the system is surging. When a human operator recognizes that a new energy peak is being approached, he or she will want to act quickly to avoid reaching the peak and will make a decision to reduce power to one or more power consumers in the system. The human operator is essentially incapable in a limited amount of time of consulting or studying the many different energy users (such as energy-using devices or apparatuses such as air-conditioners, etc.) to ascertain the status of each. A human operator practically speaking can do no more than, at best, execute one or more energy-reducing commands—for at least the reason that the luxury of time is not present.
Software systems that reduce energy consumption in building have been available for many years. These systems work by connecting various pieces of energy-consuming equipment to a computer, which allows the building manager to monitor consumption, and, if necessary, manually reduce it. More sophisticated systems allow third party “service bureaus” to provide these functions for building owners, but they still rely on intensive human intervention to be effective. Heretofore, the analysis and management of energy consumption has been a manual process. Computers and software systems have been able to collect data on energy consumption in particular facilities or on individual pieces of equipment for years. But human beings have had to analyze that information, and decide what action to take to reduce energy consumption. And because many factors affect energy consumption at any given moment—the weather outside, the number of people inside, etc.—it has never been possible to accurately and precisely adjust energy consumption in real time. For example, the Woolard et al. system seeks to use three dimensional facilities navigation tools, energy consumption analysis processes, TCP/IP communication and a World Wide Web (WWW)-based interface, but it is based on sub-systems each of which “performs operations which permit an employee of the entity to control and manage its facilities including its energy consumption.” Id., column 2, lines 26-29 (emphasis added).
The electricity crisis in California in 2001 provides a vivid illustration. Although many buildings and factories in the state have energy management systems, the only option available to power suppliers and commercial consumers trying to prevent wholesale network collapse was literally to turn out the lights in “brownouts” and rolling blackouts. The energy management systems in place and the people who monitor them on a daily basis were simply not capable of analyzing all of the potential alternative for reducing energy consumption and doing so quickly. The only choice was to shut down whole systems and businesses. Power outages, even planned power outages, have highly disruptive effects, such as disrupting telephone and computer network equipment, data inaccessibility, etc.
The various government and quasi-government entities charged with ensuring energy availability will continue to push users to curtail their electric power usage in order to avoid the devastating impact of blackouts, either actual or threatened. Avoidance of power outages by large users of power is sought, as having many benefits. Businesses need to have reliable sources of energy. Governments face social and political consequences of chronic energy shortages. Power suppliers cannot meet the demand for electricity in their areas, without building large power-generating reserves, which is not an optimal solution. Thus, it will be appreciated that there are many challenges in the areas of energy consumption, energy shortages, and energy management that remain to be addressed.